Hybrid transcription of audio, which involves human transcribers reviewing and correcting transcriptions generated by automatic speech recognition (ASR) systems, has emerged as an efficient way to provide accurate transcription services in a timely manner. Hybrid transcription is especially suited for dealing with transcription of large audio files, such as transcribing recordings of legal depositions. Often there is a large pool of transcribers available to work with, but it is not always clear who to choose for a transcription job. If the wrong transcriber is chosen, such as a transcriber that is not familiar with an accent spoken in the audio and/or the subject matter of the audio, this may prolong the transcription process as well as result is less accurate transcriptions. Thus, there is a need for a way guide selection of appropriate transcribers to handle audio with specific characteristics.